Single-cell analysis and stochastic modelling unveil large cell-to-cell variability in influenza A virus infection

• DOI: 10.1038/ncomms9938
• Publication Date: 2015-11-20T10:40:48Z
• Authors: Frank S. Heldt; Sascha Y. Kupke; Sebastian Dorl; Udo Reichl; Timo Frensing
• Keywords: 0301 basic medicine; Cell Survival; Models, Theoretical; Article; Cell Line; 3. Good health; Kinetics; 03 medical and health sciences; Influenza A virus; Influenza, Human; Animals; Humans; Single-Cell Analysis

Abstract Biochemical reactions are subject to stochastic fluctuations that can give rise cell-to-cell variability. Yet, how this variability affects viral infections, which themselves involve noisy reactions, remains largely elusive. Here we present single-cell experiments and simulations reveal a large heterogeneity between influenza A virus (IAV)-infected cells. In particular, experimental data show progeny titres range from 1 970 plaque-forming units intracellular RNA (vRNA) levels span three orders of magnitude. Moreover, the segmentation IAV genomes seems increase susceptibility their replication noise, since level different genome segments vary substantially within cell. addition, suggest abortion entry random degradation vRNAs result in fraction non-productive cells after single-hit infection. These results challenge current beliefs cell population measurements deterministic an accurate representation infections.